Uncertainty Data in Interval-Valued Fuzzy Set Theory Properties, Algorithms and Applications /

This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov's intuitionistic fuzzy sets and their use in uncertainty models involving imperfect o...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Pękala, Barbara (Συγγραφέας, http://id.loc.gov/vocabulary/relators/aut)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2019.
Έκδοση:1st ed. 2019.
Σειρά:Studies in Fuzziness and Soft Computing, 367
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Uncertainty Data in Interval-Valued Fuzzy Set Theory  |h [electronic resource] :  |b Properties, Algorithms and Applications /  |c by Barbara Pękala. 
250 |a 1st ed. 2019. 
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490 1 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 367 
505 0 |a Introduction to Fuzzy Sets -- Interval-Valued Fuzzy Relations -- Applications -- Summary and Open Problem. 
520 |a This book offers an introduction to fuzzy sets theory and their operations, with a special focus on aggregation and negation functions. Particular attention is given to interval-valued fuzzy sets and Atanassov's intuitionistic fuzzy sets and their use in uncertainty models involving imperfect or unknown information. The theory and application of interval-values fuzzy sets to various decision making problems represent the central core of this book, which describes in detail aggregation operators and their use with imprecise data represented as intervals. Interval-valued fuzzy relations, compatibility measures of interval and the transitivity property are thoroughly covered. With its good balance between theoretical considerations and applications of originally developed algorithms to real-world problem, the book offers a timely, inspiring guide to mathematicians and engineers developing new decision making models or implementing/applying existing ones to a wide range of applications involving imprecise or incomplete data. . 
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